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Record W2067626447 · doi:10.1364/oe.22.003777

Polarization rotator-splitters in standard active silicon photonics platforms

2014· article· en· W2067626447 on OpenAlexafffund
Wesley D. Sacher, Tymon Barwicz, B. J. Taylor, Joyce K. S. Poon

Bibliographic record

VenueOptics Express · 2014
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolarization rotatorPolarization (electrochemistry)OpticsSilicon photonicsSilicon on insulatorPhotonicsPower dividers and directional couplersOptoelectronicsSplitterSiliconMaterials sciencePhysicsBirefringence

Abstract

fetched live from OpenAlex

We demonstrate various silicon-on-insulator polarization management structures based on a polarization rotator-splitter that uses a bi-level taper TM0-TE1 mode converter. The designs are fully compatible with standard active silicon photonics platforms with no new levels required and were implemented in the IME baseline and IME-OpSIS silicon photonics processes. We demonstrate a polarization rotator-splitter with polarization crosstalk < -13 dB over a bandwidth of 50 nm. Then, we improve the crosstalk to < -22 dB over a bandwidth of 80 nm by integrating the polarization rotator-splitter with directional coupler polarization filters. Finally, we demonstrate a polarization controller by integrating the polarization rotator-splitters with directional couplers, thermal tuners, and PIN diode phase shifters.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.215
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations231
Published2014
Admission routes2
Has abstractyes

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